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v0.2.1
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README.md

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@@ -42,9 +42,9 @@ conda install torchdrug -c milagraph -c conda-forge -c pytorch -c pyg
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### From Pip ###
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```bash
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pip3 install torch==1.9.0
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pip3 install torch-scatter torch-cluster -f https://pytorch-geometric.com/whl/torch-1.9.0+cu102.html
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pip3 install torchdrug
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pip install torch==1.9.0
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pip install torch-scatter torch-cluster -f https://pytorch-geometric.com/whl/torch-1.9.0+cu102.html
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pip install torchdrug
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```
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To install `torch-scatter` for other PyTorch or CUDA versions, please see the

conda/torchdrug/meta.yaml

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package:
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name: torchdrug
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version: 0.2.0
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version: 0.2.1
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source:
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path: ../..

doc/source/api/utils.rst

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Helper functions
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----------------
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.. currentmodule:: torchdrug.utils.doc
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.. currentmodule:: torchdrug.utils
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.. autofunction:: copy_args

doc/source/installation.rst

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============
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TorchDrug can be installed on either Linux, Windows or macOS. It is compatible with
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Python 3.7/3.8/3.9 and PyTorch >= 1.8.0.
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3.7 <= Python <= 3.10 and PyTorch >= 1.8.0.
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For Windows
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.. code:: bash
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pip3 install torch
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pip install torch
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To install ``torch-scatter``, we need to check the version of PyTorch and CUDA.
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.. code:: bash
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pip3 install torch-scatter torch-cluster -f https://pytorch-geometric.com/whl/torch-1.8.0+cu102.html
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pip install torch-scatter torch-cluster -f https://pytorch-geometric.com/whl/torch-1.8.0+cu102.html
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Replace the versions in the above url according to your case. If you don't have GPUs
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or CUDA installed, treat the CUDA version in the url as ``cpu``. See
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.. code:: bash
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pip3 install torchdrug
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pip install torchdrug
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From Source
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-----------
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Apple Silicon (M1/M2 Chips)
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---------------------------
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PyTorch supports Apple silicon from version 1.13. While `torch-scatter` and `torch-cluster` don't have pre-compiled binaries for Apple silicon, we can compile them from their sources. See https://github.com/rusty1s/pytorch_scatter/issues/241 for more details.
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PyTorch supports Apple silicon from version 1.13. While `torch-scatter` and
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`torch-cluster` don't have pre-compiled binaries for Apple silicon, we can compile
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them from their sources. See https://github.com/rusty1s/pytorch_scatter/issues/241
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for more details.
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.. code:: bash
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docker/Dockerfile

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FROM pytorch/pytorch:1.8.1-cuda11.1-cudnn8-devel
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# metainformation
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LABEL org.opencontainers.image.version = "0.2.0"
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LABEL org.opencontainers.image.version = "0.2.1"
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LABEL org.opencontainers.image.authors = "TorchDrug Team"
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LABEL org.opencontainers.image.source = "https://github.com/DeepGraphLearning/torchdrug"
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LABEL org.opencontainers.image.licenses = "Apache License 2.0"

setup.py

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long_description_content_type="text/markdown",
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url="https://torchdrug.ai/",
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author="TorchDrug Team",
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version="0.2.0",
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version="0.2.1",
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license="Apache-2.0",
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keywords=["deep-learning", "pytorch", "drug-discovery"],
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packages=setuptools.find_packages(),

torchdrug/__init__.py

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handler.setFormatter(format)
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logger.addHandler(handler)
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__version__ = "0.2.0"
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__version__ = "0.2.1"

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